Marketing, Data Science Analyst

Transat AT•Montreal, QC

23h•Hybrid

About The Position

In collaboration with the Marketing Planning leadership team, the Data Scientist plays a key role in leading marketing measurement, experimentation, and performance insights across integrated and cross-channel initiatives. The incumbent strengthens Air Transat’s measurement foundation to support better decision-making related to marketing investment, campaign planning, and performance optimization. They develop scalable measurement frameworks, advance experimentation practices, and generate insights that clarify performance drivers, incremental impact, and future investment opportunities. Working closely with Marketing Planning, Media Strategy, Performance Marketing, Revenue Management, and Finance, the Data Scientist contributes to a more rigorous, data-driven approach to decision-making. They tackle complex business questions related to campaign effectiveness, incrementality, forecasting, demand generation, and budget allocation, while building repeatable processes and scalable reporting. Success in this role requires strong technical and statistical expertise, solid business acumen, and the ability to translate complex analyses into clear, actionable recommendations that influence strategic and investment decisions.

Requirements

Bachelor’s degree in Data Science, Statistics, Mathematics, Analytics, or a related field.
Minimum of 5 years of experience in marketing analytics, data science, experimentation, or performance measurement in a cross-channel environment.
Experience developing measurement frameworks, designing experiments, and translating insights into business recommendations.
Strong applied statistics expertise (regression, hypothesis testing, confidence intervals, model validation, uncertainty interpretation).
Advanced understanding of experimentation and incrementality (control vs. exposed, geo tests, bias, causal inference).
Experience with forecasting (trend, seasonality, baseline vs. incremental) using tools such as ARIMA, SARIMAX, or Prophet.
Experience with advanced marketing analytics such as Marketing Mix Modeling (MMM), attribution, or contribution analysis.
Strong proficiency in Python and SQL for analysis, automation, and data workflows.
Excellent command of MS Office tools (Word, Excel, Outlook, Teams) and comfort with digital collaboration tools and AI (e.g., Copilot).
Ability to quickly learn and adapt to new technologies.
Oral and written fluency in French and English
A good knowledge of French is required for positions in Quebec. The incumbent will be required to communicate and collaborate frequently in English, both orally and in writing, with colleagues, customers, and other stakeholders in Quebec, the rest of Canada, and internationally.

Responsibilities

Own and evolve marketing measurement frameworks across campaigns, audiences, channels, and business lines.
Define measurement plans (KPIs, success criteria, benchmarks, attribution logic, incrementality) and ensure they are integrated upfront in campaign planning.
Distinguish between platform-reported performance, attributed performance, and true incremental business impact.
Partner with marketing teams to define and execute the Test & Learn roadmap, including hypothesis development.
Design and analyze experiments (geo tests, audience holdouts, pre/post analyses) including power analysis, sample sizing, and expected lift.
Apply statistical and causal inference methods to generate robust insights (lift, iROAS, confidence levels, limitations).
Develop and leverage advanced methods, including Marketing Mix Modeling (MMM), to optimize marketing investment allocation.
Assess campaign effectiveness and deliver deep-dive insights on performance drivers, customer behavior, and demand trends.
Build and enhance dashboards, reporting tools, and data integration while ensuring quality and consistency.
Support forecasting (demand, bookings, campaign impact) and automate reporting using Python, SQL, and BI tools.
Collaborate with cross-functional stakeholders to support decision-making and translate analysis into actionable recommendations.